Reader Comments and Retorts

Statements posted here are those of our readers and do not represent the BaseballThinkFactory. Names are provided by the poster and are not verified. We ask that posters follow our submission policy. Please report any inappropriate comments.

If you think data-driven machine learning nonsense is bad in the commercial (or uh, "sports analysis hobby") world, I think it may be actually ruining (biological) science.
Ironically - because it kinda works. If you are interested in predicting things ("especially about the future") it has significant utility. But science (to me) isn't about predicting the future. That's astrology. It's about understanding the WHYS of cause and effect. Something that (we used to call) statistics is very, very bad at. Even specialized rule-based "deep learning".

compicating? You can't realistically complicate biology. It's absurdly fractal in it's complexity. I mean "ruining" because (as near as I can tell) using models like this are so opaque as to prevent any true understanding of the physical-chemical processes involved.

Been seeing ads for "Solution Designer" lately ... near as I can tell, what was called a Business Analyst 5-10 years ago. I just love the title and the way the ads are written -- basically they're looking for someone who can just float around from one problem to the next and provide a solution ... whether it's a more efficient production process, keeping Bobby from groping Susie, regularly running out of TP in the men's room or that Jake Arrieta has lost a couple of miles off his fastball ... no matter your problem, Solution Designer will fix it.

Now statistics (what statisticians call statistics ... or at least applied statisticians) loves to test your supposed understanding of the WHYS against real data, in the presence of uncertainty, and estimate and evaluate the remaining uncertainty and explore whether in fact the assumptions of the model are met then predict out-of-sample outcomes from your brilliant model (while acknowledging the uncertainty). There's nothing statisticians love more than modeling except possibly demonstrating the model is full of crap. Very few "real" statisticians consider machine learning to be all that interesting and spend most of their time groaning about how data scientists don't know crap about statistics (generally true).

But, y'know, the money is where the money is, so they're generally more than happy to train the data scientists of tomorrow.

Been seeing ads for "Solution Designer" lately ... near as I can tell, what was called a Business Analyst 5-10 years ago.

The re-branding of corporate job titles, years (decades?) in the making, continues its march unabated. Everyone used to be an analyst, whether or not they actually analysed anything. Now they are architects (whether or not they actually design anything) or solution designers or consultants. The verb solutioning seems to have been invented and as far as I can gather, it means solving a problem by finding the person who can actually do the work and having them do it.

And any schmuck who can do a VLOOKUP in Excel is now happy to claim they are doing analytics when it's actually much closer to what Jethro Bodine would have called ciphering.

nice writeup, Walt. Kinda describes me; a statistician at heart, but cleverly disguised with an engineering degree, since almost 40 yrs people all said that was where the jobs were. Which was true I suppose, but I do get to play with numbers and uncertainties and sample sizes a lot. I'm in the flight test world, and flight testing is reeeeally expensive.

I would someday live in a world where 'solution' is a verb and 'spend' is a noun

Someone like John McWhorter might argue that this is the natural evolution of language (nouns becoming verbs and verbs becoming nouns). Doesn't make it any less painful to endure, though, especially in a corporate context where language choices are meant to dress up simple ideas to look like rocket science.

I love consultants, which is what these people are but with newer titles, they basically get paid way more than companies are willing to spend on their actual employees and they usually tell you things you already know and ways of accomplishing goals that you already know. It's like a diet. Everyone knows how to lose weight the real trick is actually losing weight and consultants don't do that for you. They basically tell you to do 30 push ups and eat less, now where's my check?

Kudos to James Fegan for overhearing an offhand comment by a marginal reliever and following up. He got a story that no other reporter was seeking, and some perspective into how players talk to each other about their craft.

It is an awesome job... truly - I love it. You get to say that you're too smart and valuable to write code when it's time to ask for a raise; while you also get to fall back on being too dumb to write code if things go wrong and you want to escape culpability.

When I finally got this role ~5 years ago - I went from having a job to a career.

This is an amazing article. Discussed it a couple days ago on Soxtalk.com. It's worth the sub cost for the Athletic almost by itself. And a hat tip to Lloyd McClendon, who apparently noticed how Farquhar was getting guys out up in the zone with his mediocre 4 seamer before they had the data to confirm it.